Cross-Domain Self-Supervised Deep Learning for Robust Alzheimer's Disease Progression Modeling. (arXiv:2211.08559v1 [cs.CV])

Developing successful artificial intelligence systems in practice depends
both on robust deep learning models as well as large high quality data.
Acquiring and labeling data can become prohibitively expensive and
time-consuming in many real-world applications such as clinical disease models.
Self-supervised learning has demonstrated great potential in increasing model
accuracy and robustness in small data regimes. In addition, many clinical
imaging and disease modeling applications rely heavily on regression of
continuous quantities. However, the applicability of self-supervised learning
for these …

alzheimer's arxiv deep learning disease modeling